Associations between the portion sizes of food groups consumed and measures of adiposity in the British National Diet and Nutrition Survey
Bibliographic record
Abstract
The objective of the present study was to examine the associations between the portion sizes of food groups consumed with measures of adiposity using data from the National Diet and Nutrition Survey of British adults. Seven-day weighed dietary records, physical activity diaries and anthropometric measurements were used. Foods eaten were assigned to thirty different food groups and analyses were undertaken separately for men and women. The median daily portion size of each food group consumed was calculated. The potential mis-reporting [corrected] of dietary energy intake (EI) was identified using the following equation: EI--estimated energy requirements/EER [corrected] x 100 = percentage of under-reporting (UR) of energy needs. Multinomial logistic regression (adjusted for age, social class, physical activity level and UR) was used to determine the portion sizes of food groups most strongly associated with obesity status. Few positive associations between the portion sizes of food groups consumed and obesity status were found. However, UR was prevalent, with a median UR of predicted energy needs of 34 and 33 % in men and women, respectively. After the adjustment was made for UR, more associations between the food groups and obesity status became apparent in both sexes. The present study suggests that the true effect of increased portion size of foods on obesity status may be masked by high levels of UR. Alternatively, these data may indicate that an increased risk of obesity is not associated with specific foods/food groups but rather with an overall increase in the range of foods and food groups being consumed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".